[R] The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks

submitted by /u/pcaversaccio [link] [comments]

1m

[P] I built an art installation using a Nvidia Xavier and a StyleGAN trained on abstract art

Play video on reddit submitted by /u/maktattengil [link] [comments]

1m

[Research][Discussion] Roadmap for a Research Scientist position

Hello everyone, I'm currently in my 4th year of a PhD in CSE(AI/ML). I'm very much interested in the position of a research scientist. Since I have hardly one year for graduation, I would like know the roadmap to achieve a good role after graduation. I would like to ask suggestions, advices and recommendations from the experts. submitted by /u/bewilderedatom...

3h

[D] CNN on mel spectrograms vs. WaveNet for audio recognition?

So I am creating an app in which I intend to rank a user-inputed song according to its similarity to Jimi Hendrix songs. Similar projects have been done before and, from what I've seen, the go-to approach is to train a CNN on mel spectrograms. This is also what was suggested to me. Well, today I was talking about this in an AI discord and someone told...

3h

[R] Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning

submitted by /u/hardmaru [link] [comments]

3h

[R] GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation (works for videos too!)

submitted by /u/Illustrious_Row_9971 [link] [comments]

4h

[D] How do models like ARMA and ARIMA fare against "sporadic memory"?

Is it fair to assume that standard time series models like the ARMA and the ARIMA model are not well designed to handle "sporadic and irregular" memory patterns? As I understand, these models are usually used to handle data with well-behaved notions of "trends" and "seasonality" (e.g. you specify these in a given ARIMA model) . When you start to deal...

4h

[D] Creating neural network to solve for equations

Hi Team, I have posted this question on one forums and would appreciate if someone can help in answering it. https://datascience.stackexchange.com/questions/96827/creating-neural-network-to-solve-for-equations The v1 variable is a mathematical expression. Currently, I am using hyperopt to solve for these parameters and am using v1,v2,v3 in regression...

12h

[P] Megatron-LM - Annotated Paper!!

Megatron-LM provides a simple yet innovative approach on how to parallelize models to train large (multi-billion parameters) language models and efficiently use GPU memory during scaling. The key point is that it does not require any major modifications (like compilation or an entirely new framework) to implement this in the existing code. It also suggested...

12h

[D] Over/Under sampling proving unhelpful in classification problem with Imbalanced classes

I'm working on data with severe class imbalance (1% is minority class) I've tried re-sampling with ratios like 1:1, 2:3..Tried over/under sampling. Getting f1 score of max 15% (Both precision and recall are poor). I've tried different algorithms, started from ridge regression, tried random forest, boosting methods. I have 25k data points to work on....

13h